Features

Everything you need for production-ready GraphQL APIs

Core Features

⚡

Rust Pipeline

PostgreSQL → Rust → HTTP. No Python in the hot path. Other frameworks can't do this.

  • ✅ 7-10x faster JSON transformation
  • ✅ No GIL contention, compiled performance
  • ✅ Zero Python serialization overhead
  • ✅ Direct database-to-HTTP response path
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🔒

Security by Architecture

JSONB views define exactly what's exposed. Impossible to accidentally leak sensitive fields.

  • ✅ Explicit field whitelisting in views
  • ✅ No ORM over-fetching risks
  • ✅ What's not in the view cannot be queried
  • ✅ Two-layer verification (SQL + Python)
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🎯

Zero N+1 by Design

PostgreSQL composes nested data once in JSONB. Views contain all relations.

  • ✅ One query regardless of GraphQL complexity
  • ✅ DataLoader is unnecessary
  • ✅ Nested relations pre-composed in views
  • ✅ No resolver chains to optimize
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🤖

AI-Native Development

SQL + Python are massively trained languages. LLMs generate correct FraiseQL code on first try.

  • ✅ Complete business logic in one file
  • ✅ No hidden ORM magic to confuse LLMs
  • ✅ 30-50% fewer tokens than Python
  • ✅ Stable syntax since the 1990s
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💰

Simplified Infrastructure

Three features that simplify your stack and eliminate infrastructure.

  • ✅ Table views eliminate Redis
  • ✅ Cascade eliminates refetch queries
  • ✅ tb_entity_change_log = built-in audit
  • ✅ One database, ACID everywhere
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🏗️

Database-First CQRS

Views for queries, functions for mutations. Business logic in PostgreSQL with ACID guarantees.

  • ✅ Clear separation of reads and writes
  • ✅ No ORM abstraction layer
  • ✅ Structured error handling
  • ✅ Enterprise audit trails built-in
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🎨

Auto-Generated Filters

Define your types, get 35+ WHERE operators automatically. Zero filter boilerplate.

  • ✅ String → contains, startsWith, regex
  • ✅ Date → gt, lt, between, ranges
  • ✅ IP → subnet, contains, overlaps
  • ✅ AND/OR/NOT logical operators
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🎯

50+ Specialized Types

Native PostgreSQL types with type-aware operators no other GraphQL framework has.

  • ✅ IPv4/IPv6 with subnet operations
  • ✅ LTree hierarchies with ancestor queries
  • ✅ DateRange with overlap/containment
  • ✅ CUSIP/ISIN, pgvector for semantic search
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📡

Automatic Persisted Queries

70% bandwidth reduction. Skip query parsing. Optional security hardening.

  • ✅ Send hash instead of full query text
  • ✅ Pre-parsed queries, lookup only
  • ✅ Persisted-only mode blocks arbitrary queries
  • ✅ Apollo APQ specification compatible
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🛡️

Query Authorization

Register allowed queries via APQ. Block arbitrary GraphQL in production.

  • ✅ Persisted-only mode whitelists queries
  • ✅ Block introspection in production
  • ✅ Zero-parsing for registered queries
  • ✅ Security events logged
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Additional Features

🛡️

Security First

Built-in protection against common vulnerabilities.

  • • SQL injection prevention
  • • Input validation layer
  • • Parameterized queries only
  • • Pattern detection for malicious input
🔐

Flexible Authentication

Pluggable auth system with built-in providers.

  • • Auth0 integration
  • • Development auth mode
  • • Custom provider support
  • • Role-based access control
🚀

Code Generation

Generate boilerplate code from your types.

  • • Database migrations
  • • CRUD operations
  • • GraphQL schema export
  • • Type-safe repositories
📊

Performance Optimized

Designed for speed from the ground up.

  • • Single query for nested data
  • • Connection pooling
  • • Query result caching
  • • N+1 query elimination
🔧

Developer Experience

Built by developers, for developers.

  • • Full type hints
  • • GraphQL Playground
  • • Detailed error messages
  • • Hot reloading
🌐

Production Ready

Everything you need for real-world deployments.

  • • FastAPI integration
  • • CORS support
  • • Health checks
  • • Configurable via environment
🔍

Vector Search (pgvector)

Native PostgreSQL vector similarity search with 9+ distance operators.

Learn more →
🌊

GraphQL Cascade

No refetch after mutations. 50% fewer round-trips. Automatic cache updates for Apollo & Relay.

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🦜🦙

LangChain & LlamaIndex

Build RAG applications with your favorite AI framework.

Learn more →
🌱

Energy Efficiency

10-100x fewer CPU cycles. Run on smaller hardware. Lower carbon footprint.

Learn more →

Feature Comparison

Feature FraiseQL Traditional ORM + GraphQL
JSON Transformation ✅ Rust (7-10x faster) ❌ Python serialization
N+1 Query Problem ✅ Impossible by design ⚠️ Requires DataLoader
Field Exposure Control ✅ View-enforced whitelist ❌ ORM can over-fetch
Recursion Depth Attacks ✅ Structurally impossible ⚠️ Middleware required
LLM Code Generation ✅ SQL + Python (native) ⚠️ Framework-specific DSLs
Database Support ⚠️ PostgreSQL only ✅ Multiple databases

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